Method for determining predisposition to pulmonary infection

ABSTRACT

Provided herein are methods and materials for diagnosing a subject&#39;s predisposition for pulmonary infection in a CF subject by detecting a pulmonary infection genetic marker. Pulmonary infection markers have been identified in the IL-1 gene cluster and may be useful in predicting CF disease progression and assessing a CF subject&#39;s response to therapy.

CROSS-RELATED APPLICATIONS

The present application claims the benefit of the filing date ofprovisional application 60/926,649, filed on Apr. 27, 2007, which isincorporated by reference in its entirety.

FEDERALLY SPONSORED RESEARCH

This invention was made with government support under NHLBI K23 grantnumber K23HL074202. The government has certain rights in the invention.

FIELD OF THE INVENTION

The present invention relates to the IL-1 gene family and itsassociation with lung disease in cystic fibrosis patients.

BACKGROUND

Progressive pulmonary disease associated with chronic bacterialinfection and airway inflammation is the major cause of morbidity andmortality in cystic fibrosis (CF) patients. CF lung disease may becharacterized by chronic bacterial infection, with prevalence ofinfection increasing with age. CF patients with the most common CFtransmembrane conductance regulator (CFTR) mutation, ΔF508, a deletionof a phenylalanine at position F508 of CFTR, often have markedlydifferent clinical courses; some have less aggressive lung disease andsurvive into their 50s, while others have a precipitous decline in lungfunction and die of respiratory failure in their early 20s. Whataccounts for this phenotypic heterogeneity is unclear.

Early assessment of lung disease severity may present the bestopportunity for treatment intervention. With the development of genetictesting, it is possible to identify genetic markers that will beindicative of a propensity to develop disease or indicative of a diseasestate. There remains a need to identify one or more genetic markers thatare associated with lung disease in CF patients. These genetic markersmay represent allelic variants, which may be useful in diagnosing lungdisease severity, and whose products may be targeted for earlyintervention therapy.

SUMMARY OF THE INVENTION

Provided herein is a method for determining a CF subject'spredisposition for pulmonary infection. The method may compriseproviding a nucleic acid-containing sample from a cystic fibrosispatient. A determination may be made as to whether the sample comprisesa pulmonary infection marker. The pulmonary infection marker may be inan IL-1 gene cluster. The IL-1 gene cluster may comprise the genesIL-1α, IL-1RN, IL-1R1, and IL-1β. The presence of a pulmonary infectionmarker (“PI-marker”) may indicate that the subject has a predispositionfor pulmonary infection. The marker may be a SNP as shown inrs1143639^(256T) (SEQ ID NO:3), wherein the SNP corresponds tonucleotide 256 of SEQ ID NO:3 and is a thymine; rs1143639^(256C) (SEQ IDNO:4), wherein the SNP corresponds to nucleotide 256 of SEQ ID NO:4 andis a cytosine; rs1143634^(401A) (SEQ ID NO:1), wherein the SNPcorresponds to nucleotide 401 of SEQ ID NO:1 and is an adenine;rs1143634^(401G) (SEQ ID NO:2), wherein the SNP corresponds tonucleotide 401 of SEQ ID NO:2 and is a guanine; rs2228139^(301G) (SEQ IDNO:5), wherein the SNP corresponds to nucleotide 301 of SEQ ID NO:5 andis a guanine; rs2228139^(301C) (SEQ ID NO:6), wherein the SNPcorresponds to nucleotide 301 of SEQ ID NO:6 and is a cytosine;rs17561^(256A) (SEQ ID NO:7), wherein the SNP corresponds to nucleotide256 of SEQ ID NO:7 and is an adenine; rs17561^(256C) (SEQ ID NO:8),wherein the SNP corresponds to nucleotide 256 of SEQ ID NO:8 and is acytosine; rs3917356^(256C) (SEQ ID NO:9), wherein the SNP corresponds tonucleotide 256 of SEQ ID NO:9 and is a cytosine; rs3917356^(256T) (SEQID NO:10), wherein the SNP corresponds to nucleotide 256 of SEQ ID NO:10and is a thymine; rs1143633^(401T) (SEQ ID NO:11), wherein the SNPcorresponds to nucleotide 401 of SEQ ID NO:11 and is a thymine;rs1143633^(401C) (SEQ ID NO:12), wherein the SNP corresponds tonucleotide 401 of SEQ ID NO:12 and is a cytosine; rs3917368^(301T) (SEQID NO:13), wherein the SNP corresponds to nucleotide 301 of SEQ ID NO:13and is a thymine; rs3917368^(301C) (SEQ ID NO:14), wherein the SNPcorresponds to nucleotide 301 of SEQ ID NO:14 and is a cytosine;rs4252019^(501T) (SEQ ID NO:15), wherein the SNP corresponds tonucleotide 501 of SEQ ID NO:15 and is a thymine; rs4252019^(501C) (SEQID NO:16), wherein the SNP corresponds to nucleotide 501 of SEQ ID NO:16and is a cytosine; rs2071374^(301G) (SEQ ID NO:17), wherein the SNPcorresponds to nucleotide 301 of SEQ ID NO:17 and is a guanine; andrs2071374^(301T) (SEQ ID NO:18), wherein the SNP corresponds tonucleotide 301 of SEQ ID NO:18 and is a thymine. The marker may beamplified. Amplification of a marker may be via polymerase chainreaction and primers. The marker may be detected by sequence analysis oroligonucleotide probe hybridization. The oligonucleotide probe may belabeled. The oligonucleotide may consist of a sequence selected from thegroup of SEQ ID NO:1, SEQ ID NO:2, SEQ ID NO:3, SEQ ID NO:4, SEQ IDNO:5, SEQ ID NO:6, SEQ ID NO:7, SEQ ID NO:8, SEQ ID NO:9, SEQ ID NO:10,SEQ ID NO:11, SEQ ID NO:12, SEQ ID NO:13, SEQ ID NO:14, SEQ ID NO:15,SEQ ID NO:16, SEQ ID NO:17, and SEQ ID NO:18, or a fragment thereof.

A marker may indicate a subject's predisposition to severe pulmonaryinfection. The pulmonary infection, whether severe or mild, may beassociated with bacterial lung colonization. The infection may be causedby Pseudomonas aeruginosa. A PI-marker associated with severe pulmonaryinfection may be rs3917356^(256C), rs1143633^(401T), rs4252019^(501T),and/or rs1143639^(256T). A marker may indicate a subject'spredisposition to mild pulmonary infection. Such a marker may bers2071374^(301G). A marker may be common in one geographical, ethnic,gender, and/or age group, and may be more rare, or non-existent, inanother. The marker rs2228139^(301G) and/or rs1143634^(401A) mayindicate a female subject's predisposition to severe lung infection. Themarker rs17561^(256A) may indicate a male subject's predisposition tosevere lung infection. Severe lung infection may be further associatedwith an adjusted forced expiratory volume in 1 second (FEV₁). The FEV₁may be a value percentage higher or lower than a predicted percentagefor a control subject. The FEV₁ may be adjusted according togeographical data, ethnicity, gender, and/or age of the subject beingtested. Severe lung disease or lung infection may be associated withPseudomonas aeruginosa lung colonization.

Also provided herein is a method of treating a subject identified ashaving a predisposition to pulmonary lung infection and/or lung disease.The subject may have an FEV₁ value that is lower than a predictedpercentage for a control subject. The FEV₁ may be adjusted according togeographical data, ethnicity, gender, and/or age of the subject beingtested. The subject may have pulmonary infection associated withPseudomonas aeruginosa lung colonization. The method may compriseadministering an anti-infection agent to the subject. The anti-infectionagent may be an anti-inflammatory agent or an antibacterial agent. Theanti-inflammatory agent may be an IL-1 blocker such as rilonacept,anakinra, and/or Zn-protoporphyrin (ZnPP). The antibacterial agent maybe an antibiotic such as an aminoglycoside, amoxicillin, levofloxacin,dicloxacillin, cephalexin, amoxicillin/clavulanate, erythromycin,clarithromycin, azithromycin, clindamycin, cefuroxime axetil, cefprozil,cefixime, cefpodoxime proxetil, loracarbef, ciprofloxacin, tobramycin,colistin, trimethoprim/sulfamethoxazole, doxycycline, minocycline,cefazolin, nafcillin, vancomycin, β-lactam, ceftazidime, ticarcillin,piperacillin, imipenem, meropenem, aztreonam, an aminoglycoside,amikacin, merpenem, ceftazidime, chloramphenicol,ticarcillin/clavulanate, aztreonam, imipenem, a polypeptide antibiotic,and/or meropenem. The polypeptide antibiotic may be of the polymyxinclass of antibiotics.

Also provided herein is a kit for performing a method for diagnosingseverity of lung disease in a CF patient. The kit may comprise a meansfor collecting a DNA sample, a means for detecting a SNP in an allele, acontrol sample, and instructions for performing the method of diagnosis.The control sample may comprise nucleic acid selected from the groupconsisting of SEQ ID NO:1, SEQ ID NO:2, SEQ ID NO:3, SEQ ID NO:4, SEQ IDNO:5, SEQ ID NO:6, SEQ ID NO:7, SEQ ID NO:8, SEQ ID NO:9, SEQ ID NO:10,SEQ ID NO:11, SEQ ID NO:12, SEQ ID NO:13, SEQ ID NO:14, SEQ ID NO:15,SEQ ID NO:16, SEQ ID NO:17, and SEQ ID NO:18.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows the overall mean FEV % predicted by rs1143634 genotype asadjusted for age and gender.

FIG. 2 shows the overall mean FEV % predicted by rs1143639 genotype asadjusted for age and gender.

DETAILED DESCRIPTION

The inventors have made the surprising discovery that there is anassociation between pulmonary infection in CF patients and certaingenetic markers. These genetic markers, or PI-markers, have beenidentified in the IL-1 gene cluster. The identification of a PI-markerin a CF subject may be useful in predicting CF disease progression andassessing the CF subject's response to therapy. In addition, knowledgeof a particular marker associated with a susceptibility to developing aninfection or a disease may allow one to customize the prevention ortreatment in accordance with the subject's genetic profile. A comparisonof a subject's IL-1 profile to a population profile for any particulardisorder may permit the selection or design of drugs or othertherapeutic regimens that are expected to be safe and efficacious for aparticular subject or subject population. Early detection of a PI-markermay allow the subject to delay or prevent bacterial infection. A CFsubject who has a PI-marker may be treated with an antibiotic and/oranti-inflammatory regimen.

The ability to target populations expected to show the highest clinicalbenefit, based on genetic profile, may enable the repositioning ofalready marketed drugs, the rescue of drug candidates whose clinicaldevelopment has been discontinued as a result of safety or efficacylimitations, which may be patient sub-group-specific, and/or anaccelerated and less costly development of candidate therapeutics.

The methods and materials described below use genetic analysis todetermine the presence of a PI-marker and reveal whether a CF subjectmay be predisposed to pulmonary infection.

1. DEFINITIONS

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting. As used in thespecification and the appended claims, the singular forms “a,” “and” and“the” include plural references unless the context clearly dictatesotherwise.

For the recitation of numeric ranges herein, each intervening numberthere between with the same degree of precision is explicitlycontemplated. For example, for the range of 6-9, the numbers 7 and 8 arecontemplated in addition to 6 and 9, and for the range 6.0-7.0, thenumber 6.0, 6.1, 6.2, 6.3, 6.4, 6.5, 6.6, 6.7, 6.8, 6,9, and 7.0 areexplicitly contemplated.

a. Fragment

“Fragment” as used herein may mean a portion of a reference peptide orpolypeptide or nucleic acid sequence.

b. Identical

“Identical” or “identity” as used herein in the context of two or morepolypeptide or nucleotide sequences, may mean that the sequences have aspecified percentage of residues or nucleotides that are the same over aspecified region. The percentage may be calculated by optimally aligningthe two sequences, comparing the two sequences over the specifiedregion, determining the number of positions at which the identicalresidue occurs in both sequences to yield the number of matchedpositions, dividing the number of matched positions by the total numberof positions in the specified region, and multiplying the result by 100to yield the percentage of sequence identity. In cases where the twosequences are of different lengths or the alignment produces one or morestaggered ends and the specified region of comparison includes only asingle sequence, the residues of single sequence are included in thedenominator but not the numerator of the calculation.

c. Label

“Label” or “detectable label” as used herein may mean a moiety capableof generating a signal that allows the direct or indirect quantitativeor relative measurement of a molecule to which it is attached. The labelmay be a solid such as a microtiter plate, particle, microparticle, ormicroscope slide; an enzyme; an enzyme substrate; an enzyme inhibitor;coenzyme; enzyme precursor; apoenzyme; fluorescent substance; pigment;chemiluminescent compound; luminescent substance; coloring substance;magnetic substance; or a metal particle such as gold colloid; aradioactive substance such as ¹²⁵I, ¹³¹I, ³²P, ³H, ³⁵S, or ¹⁴C; aphosphorylated phenol derivative such as a nitrophenyl phosphate,luciferin derivative, or dioxetane derivative; or the like. The enzymemay be a dehydrogenase; an oxidoreductase such as a reductase oroxidase; a transferase that catalyzes the transfer of functional groups,such as an amino; carboxyl, methyl, acyl, or phosphate group; ahydrolase that may hydrolyzes a bond such as ester, glycoside, ether, orpeptide bond; a lyases; an isomerase; or a ligase. The enzyme may alsobe conjugated to another enzyme.

The enzyme may be detected by enzymatic cycling. For example, when thedetectable label is an alkaline phosphatase, a measurement may be madeby observing the fluorescence or luminescence generated from a suitablesubstrate, such as an umbelliferone derivative. The umbelliferonederivative may comprise 4-methyl-umbellipheryl phosphate.

The fluorescent or chemiluminescent label may be a fluoresceinisothiocyanate; a rhodamine derivative such as rhodamine Bisothiocyanate or tetramethyl rhodamine isothiocyanate; a dancylchloride (5-(dimethylamino)-1-naphtalenesulfonyl chloride); a dancylfluoride; a fluorescamine (4-phenylspiro[furan-2(3H);1ÿ-(3ÿH)-isobenzofuran]-3;3ÿ-dione); a phycobiliprotein such as aphycocyanine or physoerythrin; an acridinium salt; a luminol compoundsuch as lumiferin, luciferase, or aequorin; imidazoles; an oxalic acidester; a chelate compound of rare earth elements such as europium (Eu),terbium (Tb) or samarium (Sm); or a coumarin derivative such as7-amino-4-methylcoumarin.

The label may also be a hapten, such as adamantine, fluorosceinisothiocyanate, or carbazole. The hapten may allow the formation of anaggregate when contacted with a multi-valent antibody or (strep)avidincontaining moiety. The hapten may also allow easy attachment of amolecule to which it is attached to a solid substrate.

The label may be detected by quantifying the level of a moleculeattached to a detectable label, such as by use of electrodes;spectrophotometric measurement of color, light, or absorbance; or visualinspection.

d. Linkage Disequilibrium

“Linkage disequilibrium” as used herein may mean the co-inheritance oftwo alleles at frequencies greater than would be expected from theseparate frequencies of occurrence of each allele in a given controlpopulation. The expected frequency of occurrence of two alleles that areinherited independently is the frequency of the first allele multipliedby the frequency of the second allele. Alleles that co-occur at expectedfrequencies are said to be in “linkage disequilibrium.”

e. Minor Allele Frequency

“Minor allele frequency” as used herein may mean the lowest allelefrequency at a locus that is observed in a particular population.

f. Substantially Identical

“Substantially identical,” as used herein may mean that a first andsecond protein or nucleotide sequence are at least 50%-99% identicalover a region of 8-100 or more amino acids nucleotides.

2. METHOD OF DIAGNOSIS

Provided herein is a method of determining a CF subject's predispositionfor pulmonary infection. This predisposition may be associated with agenetic marker. The detection of a marker in a nucleic acid-containingsample from the subject may be indicative of a predisposition forinfection. The pulmonary infection may be a bacterial infection. Thebacteria causing the infection may be P. aeruginosa, S. aureus, H.influenzae, B. cepacia, methicillin-resistant S. aureus, S. maltophilia,or A. xylosoxidans. The pulmonary infection may be a non-bacterialinfection. The non-bacterial infection may be a viral infection.

The pulmonary infection may be severe or mild as defined by the lowestor highest quartile of forced expired volume in 1 second (FEV₁) for age.FEV₁ may be determined by standard spirometry. Absolute values may beconverted to a percentage of the predicted volume expected for a healthyindividual of the same age, sex, and height on the basis of regressionequations. A subject having severe pulmonary infection may have a changein an adjusted FEV₁ value of greater than 10% than the predicted valuefor a subject of the same ethnicity, age, sex, and/or height. A decreaseof 10%, 11%, 12%, 13%, 14%, or 15% below the predicted value mayindicate severe pulmonary infection. A decrease of between 0.1% and 9.9%below the predicted value may indicate mild or moderate pulmonaryinfection. FEV₁ values may be assigned a disease severity group usingthe Epidemiological Study of Cystic Fibrosis (ESCF) classification forpatients in different age groups. In combination with, or independentof, FEV₁ values, pulmonary infection severity may be categorized basedupon bacterial colonization of sputum cultures obtained from the CFsubject.

a. Subject

The subject may be a human. The human may be diagnosed with cysticfibrosis. The cystic fibrosis may result from any mutation in the cysticfibrosis transmembrane conductance regulator (CFTR). The mutation may bea deletion of phenylalanine at position 508 of the CFTR (ΔF508), theresult of a three base pair deletion in the genetic code. The ΔF508mutation may result in a CFTR protein capable of conducting chloride,but either absent from the plasma membrane or insufficiently anchored inthe plasma membrane because of aberrant intracellular processing. Cysticfibrosis may develop in a ΔF508 heterozygote genetic carrier subjectwith varying severity level and may also develop at an advanced age.

b. Sample

The sample may comprise nucleic acid from the subject. The nucleic acidmay be DNA or RNA. The nucleic acid may be genomic. The sample may beused directly as obtained from the subject or following pretreatment tomodify a character of the sample. Pretreatment may include extraction,concentration, inactivation of interfering components, and/or theaddition of reagents.

Any cell type, tissue, or bodily fluid may be utilized to obtain anucleic acid sample. Such cell types, tissues, and fluid may includesections of tissues such as biopsy and autopsy samples, frozen sectionstaken for histologic purposes, blood, plasma, serum, sputum, stool,tears, mucus, saliva, hair, and skin. Cell types and tissues may alsoinclude lymph fluid, ascetic fluid, gynecological fluid, urine,peritoneal fluid, cerebrospinal fluid, a fluid collected by vaginalrinsing, or a fluid collected by vaginal flushing. A tissue or cell typemay be provided by removing a sample of cells from an animal, but canalso be accomplished by using previously isolated cells (e.g., isolatedby another person, at another time, and/or for another purpose. Archivaltissues, such as those having treatment or outcome history, may also beused. Nucleic acid purification may not be necessary.

c. PI-Marker

The PI-marker may be a genetic marker. The marker may be a deletion,substitution, insertion, or a polymorphism. The polymorphism may be asingle nucleotide polymorphism (SNP). The marker may be in an IL-1 genecluster. The IL-1 gene cluster may include the nucleic acid at or nearthe 2q13 region of human chromosome 2. The IL-1 gene cluster maycomprise the IL-1α gene, IL-1β gene, IL-1 receptor gene, and/or IL-1receptor antagonist gene. The marker may be detected in the IL-1α gene(gene accession number X03833), IL-1β gene (gene accession numberX04500), IL-1 receptor gene (gene accession number locus link ID 3554;OMIM 147810, Chromosome 2q12), or IL-1 receptor antagonist gene (geneaccession number X64532).

Within a population, a marker may be assigned a minor allele frequency.There may be variations between subject populations. A marker that iscommon in one geographical or ethnic group may be more rare in another.The marker may be overrepresented or underrepresented in a group of CFsubjects. CF subjects may be divided into groups on the basis of age,sex/gender, and/or race.

The marker may be detected as a SNP shown in rs1143639^(256T) (SEQ IDNO:3), wherein nucleotide 256 of SEQ ID NO:3 is a thymine;rs1143639^(256C) (SEQ ID NO:4), wherein nucleotide 256 of SEQ ID NO:4 isa cytosine; rs1143634^(401A) (SEQ ID NO:1), wherein nucleotide 401 ofSEQ ID NO:1 is an adenine; rs1143634^(401G) (SEQ ID NO:2), whereinnucleotide 401 of SEQ ID NO:2 is a guanine; rs2228139^(301G) (SEQ IDNO:5), wherein nucleotide 301 of SEQ ID NO:5 is a guanine;rs2228139^(301C) (SEQ ID NO:6), wherein nucleotide 301 of SEQ ID NO:6 isa cytosine; rs17561^(256A) (SEQ ID NO:7), wherein nucleotide 256 of SEQID NO:7 is an adenine; rs17561^(256C) (SEQ ID NO:8), wherein nucleotide256 of SEQ ID NO:8 is a cytosine; rs3917356^(256C) (SEQ ID NO:9),wherein nucleotide 256 of SEQ ID NO:9 is a cytosine; rs3917356^(256T)(SEQ ID NO:10), wherein nucleotide 256 of SEQ ID NO:10 is a thymine;rs1143633^(401T) (SEQ ID NO:11), wherein nucleotide 401 of SEQ ID NO:11is a thymine; rs1143633^(401C) (SEQ ID NO:12), wherein nucleotide 401 ofSEQ ID NO:12 is a cytosine; rs3917368^(301T) (SEQ ID NO:13), whereinnucleotide 301 of SEQ ID NO:13 is a thymine; rs3917368^(301C) (SEQ IDNO:14), wherein nucleotide 301 of SEQ ID NO:14 is a cytosine;rs4252019^(501T) (SEQ ID NO:15), wherein nucleotide 501 of SEQ ID NO:15is a thymine; rs4252019^(501C) (SEQ ID NO:16), wherein nucleotide 501 ofSEQ ID NO:16 is a cytosine; rs2071374^(301G) (SEQ ID NO:17), whereinnucleotide 301 of SEQ ID NO:17 is a guanine; and rs2071374^(301T) (SEQID NO:18), wherein nucleotide 301 of SEQ ID NO:18 is a thymine; or afragment thereof. See Table 1. The fragment may be between 10 and 500nucleotides, between 50 and 400 nucleotides, between 100 and 300nucleotides, between 200 and 250 nucleotides, between 10 and 50nucleotides, between 10 and 20 nucleotides, between 10 and 30nucleotides, or between 10 and 40 nucleotides in length.

TABLE 1  IL-1 Gene Cluster PI-Markers ([Minor allele/Major allele])dbSNP accession Sequence no. SEQ ID NO.GACCAGACATCACCAAGCTTTTTTGCTGTGAGTCCCG rs1143634 1 (Minor Allele)GAGCGTGCAGTTC chr2: 113306 2 (Major Allele)AGTGATCGTACAGGTGCATCGTGCACATAAGCCTCGT 521- TATCCCATGTGTC 113306721 [A/G]AAGAAGATAGGTTCTGAAATGTGGAGCACATGTTGTT TAGGTATAAAATCAGAAGGGCAGGCCTCGTGAGGCGAGGNGGCAAAATTT GATTTCTTGGAGGGGATTGAAGGTTGCACGCAGTTAAAAATTATGTTAAA rs1143639 3 (Minor Allele)TTTATTTACATTA chr2: 113304 4 (Major Allele)ATGCAAAATTGTCAAATAGACCTGTTCCCAGCTTTTC 924- CTAGGGATGGGGG 113305124 [T/C]NGGGAGAAGGTGGTTGTCTGGGAATAAGTGGTAGCAG GAGGCTGAGAAGGGCTTCATTCCATAGCATTCACTTACCTCCAGCTGTAG AGTGGGCTTATCAAACTTACCTATTTTATTTTATTTTAGAAATTCATCTT rs2228139  5 (Minor Allele)ACTGCCTC 6 (Major Allele) AGAATTAAAATAAGTGCAAAATTTGTGGAGAATGANC CTAACTTATGTTATAATG [G/C] ACAAGCCATATTTAAGCAGAAACTACCCGTTGCAGGA GACGGAGGACTTGTGTGCCCTTATATGGAGTTTTTTAAAAATGAAA ATAATGAGT TACCTAAAGCTCGAATTATACTTTGATTGAGGGCGTNATTCAGGA rs17561 7 (Minor Allele) TGAATTCGT8 (Major Allele) ATTTGATGATCCTCATAAAGTNGTATTTCACATTGCT CAGGAAGCTAAAAGGTG [A/C] TGACCTAGGCTTGATGATTTCTAAAACCATGATCACA AGTGCAGATTAATGTCTATGTACAAACACAGATGATATACACAGT CTAGTACA AACAGGGAAATAAAGAAATATGTTTTTAACAAGATTGAGGACTGGAT rs3917356  9 (Minor Allele)TATGAGGCTAGGG chr2: 113308 10 (Major Allele)GAGGCTATCACAAACTGGAATAAAATAAAGCCAGAGA 494- AAAGTGGCTGCNT 113308694 [C/T]CCAACCTGCACAACTGACCTAGCTAGGCTGATGGCTG GGCCNNCTAGGAAGGCTACTGAGCATCATATAAAACAGAAGGGACAGCAG GAATATAACATGGTAAGCCTCGTTATCCCATGTGTCNAAGAAGATAGGTT rs1143633 11 (Minor Allele)CTGAAATGTGGAG chr2: 113306 12 (Major Allele)CACATGTTGTTTAGGTATAAAATCAGAAGGGCAGGCC 598- TCGTGAGGCGAGG 113306798 [T/C]GGCAAAATTTGATTTCTTGGAGGACACCTGAGCATAT ACGGTCAAAGTCTGATGACAACACCAGTAGGGATGAAGCTGGGAGTGGGG TGGCTAagaacacTCTGTCTTCCAGACCACGTATGCTTTCCTCCACCTTT rs3917368  13 (Minor Allele)GCATCTTTTATCT chr2: 113298 14 (Major Allele)TCTGCCAGCCCAGATGCTTGCTGACTCCAGCCCAAGC 913- CTATAGGATAAGC 113299113 [T/C]ACAGCCTGTCCCTACAGACTACGCATTGCAGAATCTA AGACATCAAGTCAAGTTCGGAAGCACTTGCCTTCTCCTCTCCAGGTACAC AGGCTCTCCTGGAGgattattccaaaaagagcctcaacatgcaggcgctt rs4252019  15 (Minor Allele)attatNacttctc 16 (Major Allele) ttgcatcatcctattggccaaagccagtcaNgtggctaagtctagcccc [T/C] tgtgagaggagactNcataagagtgtgaacaccagga gacacggtcactggggccaccactgtaaccatctaccacaGGACCTGAAT CTCTGTGTGCTAATGATCACAAGTGCAGATTAATGTCTATGTACAAACA rs2071374 17 (Minor Allele)CAGATGATATACA 18 (Major Allele) CAGTCTAGTACAAACAGGGAAAATAGTTCTGGAGGGGNTATTAGGAATAT [G/T] CCAATCCAGATGAGGAAGCAAAGAGAAGTGAAATCAC CCAGTCAGCAGAACTGGTTTTCTAGGATTATCCTTGTTGTTGCTTATGTG CTTCTTTTTAAAC

d. Detection

The PI-marker may be detected in a sample derived from the patient. Manymethods are available for detecting a marker in a subject and may beused in conjunction with the herein described methods. These methodsinclude large-scale SNP genotyping, exonuclease-resistant nucleotidedetection, solution-based methods, genetic bit analyses, primer guidednucleotide incorporation, allele specific hybridization, and othertechniques. Any method of detecting a marker may use a labeledoligonucleotide.

(1) Large Scale SNP Genotyping

Large scale SNP genotyping may include any of dynamic allele-specifichybridization (DASH), microplate array diagonal gel electrophoresis(MADGE), pyrosequencing, oligonucleotide-specific ligation, or variousDNA “chip” technologies such as Affymetrix SNP chips. These methods mayrequire amplification of the target genetic region. Amplification may beaccomplished via polymerase chain reaction (PCR).

(2) Exonuclease-Resistant Nucleotide

PI-markers may be detected using a specialized exonuclease-resistantnucleotide, as described in U.S. Pat. No. 4,656,127, which isincorporated herein by reference. A primer complementary to the allelicsequence immediately 3′ to the polymorphic site may be permitted tohybridize to a target molecule obtained from the subject. If thepolymorphic site on the target molecule contains a nucleotide that iscomplementary to the particular exonuclease-resistant nucleotidederivative present, then that derivative may be incorporated onto theend of the hybridized primer. Such incorporation may render the primerresistant to exonuclease, and thereby permit its detection. Since theidentity of the exonuclease-resistant derivative of the sample may beknown, a finding that the primer has become resistant to exonucleasereveals that the nucleotide present in the polymorphic site of thetarget molecule was complementary to that of the nucleotide derivativeused in the reaction. This method may not require the determination oflarge amounts of extraneous sequence data.

(3) Solution-Based Method

A solution-based method may be used to determine the identity of aPI-marker, as described in PCT Application No. WO91/02087, which isherein incorporated by reference. A primer may be employed that iscomplementary to allelic sequences immediately 3′ to a polymorphic site.The method may determine the identity of the nucleotide of that siteusing labeled dideoxynucleotide derivatives that, if complementary tothe nucleotide of the polymorphic site, will become incorporated ontothe terminus of the primer.

(4) Genetic Bit Analysis

Genetic bit analysis may use mixtures of labeled terminators and aprimer that is complementary to the sequence 3′ to a polymorphic site. Alabeled terminator may be incorporated, wherein it is determined by andcomplementary to, the nucleotide present in the polymorphic site of thetarget molecule being evaluated. The primer or the target molecule maybe immobilized to a solid phase.

(5) Primer-Guided Nucleotide Incorporation

A primer-guided nucleotide incorporation procedure may be used to assayfor a PI-marker in a nucleic acid, as described in Nyren, P. et al.,Anal. Biochem. 208:171-175 (1993), which is herein incorporated byreference. Such a procedure may rely on the incorporation of labeleddeoxynucleotides to discriminate between bases at a polymorphic site. Insuch a format, since the signal is proportional to the number ofdeoxynucleotides incorporated, polymorphisms that occur in runs of thesame nucleotide may result in signals that are proportional to thelength of the run.

(6) Allele Specific Hybridization

Allele specific hybridization may be used to detect a PI-marker. Thismethod may use a probe capable of hybridizing to a target allele. Theprobe may be labeled. A probe may be an oligonucleotide. The targetallele may have between 3 and 50 nucleotides around the marker. Thetarget allele may have between 5 and 50, between 10 and 40, between 15and 40, or between 20 and 30 nucleotides around the marker. A probe maybe attached to a solid phase support, e.g., a chip. Oligonucleotides maybe bound to a solid support by a variety of processes, includinglithography. A chip may comprise more than one allelic variant of atarget region of a nucleic acid, e.g., allelic variants of two or morepolymorphic regions of a gene.

(7) Other Techniques

Examples of other techniques for detecting alleles include selectiveoligonucleotide hybridization, selective amplification, or selectiveprimer extension. Oligonucleotide primers may be prepared in which theknown mutation or nucleotide difference is placed centrally and thenhybridized to target DNA under conditions which permit hybridization ifa perfect match is found. Such allele specific oligonucleotidehybridization techniques may be used to test one mutation or polymorphicregion per reaction when oligonucleotides are hybridized to PCRamplified target DNA or a number of different mutations or polymorphicregions when the oligonucleotides are attached to the hybridizingmembrane and hybridized with labeled target DNA.

Allele specific amplification technology that depends on selective PCRamplification may be used in conjunction with the instant invention.Oligonucleotides used as primers for specific amplification may carrythe mutation or polymorphic region of interest in the center of themolecule. Amplification may then depend on differential hybridization,as described in Gibbs et al. (1989) Nucleic Acids Res. 17:2437-2448),which is herein incorporated by reference, or at the extreme 3′ end ofone primer where, under appropriate conditions, mismatch can prevent, orreduce polymerase extension.

Direct DNA sequencing, either manual sequencing or automated fluorescentsequencing may detect sequence variation. Another approach is thesingle-stranded conformation polymorphism assay (SSCP), as described inOrita M, et al. (1989) Proc. Natl. Acad. Sci. USA 86:2766-2770, which isincorporated herein by reference. The fragments that have shiftedmobility on SSCP gels may be sequenced to determine the exact nature ofthe DNA sequence variation. Other approaches based on the detection ofmismatches between the two complementary DNA strands include clampeddenaturing gel electrophoresis (CDGE), as described in Sheffield V C, etal. (1991) Am. J. Hum. Genet. 49:699-706, which is incorporated hereinby reference; heteroduplex analysis (HA), as described in White M B, etal. (1992) Genomics 12:301-306, which is incorporated herein byreference; and chemical mismatch cleavage (CMC) as described in GrompeM, et al., (1989) Proc. Natl. Acad. Sci. USA 86:5855-5892, which isherein incorporated by reference. A review of currently availablemethods of detecting DNA sequence variation can be found in a review byGrompe (1993), which is incorporated herein by reference. Grompe M(1993) Nature Genetics 5:111-117. Once a mutation is known, an allelespecific detection approach such as allele specific oligonucleotide(ASO) hybridization can be utilized to rapidly screen large numbers ofother samples for that same mutation. Such a technique can utilizeprobes that may be labeled with gold nanoparticles to yield a visualcolor result as described in Elghanian R, et al. (1997) Science277:1078-1081, which is herein incorporated by reference.

A rapid preliminary analysis to detect polymorphisms in DNA sequencescan be performed by looking at a series of Southern blots of DNA cutwith one or more restriction enzymes, preferably with a large number ofrestriction enzymes.

e. Amplification

Any method of detection may incorporate a step of amplifying thePI-marker. A PI-marker may be amplified and then detected. Nucleic acidamplification techniques may include cloning, polymerase chain reaction(PCR), PCR of specific alleles (ASA), ligase chain reaction (LCR),nested polymerase chain reaction, self-sustained sequence replication,transcriptional amplification system, and Q-Beta Replicase, as describedin Kwoh, D. Y. et al., 1988, Bio/Technology 6:1197, which isincorporated herein by reference.

Amplification products may be assayed by size analysis, restrictiondigestion followed by size analysis, detecting specific taggedoligonucleotide oligonucleotide primers in reaction products,allele-specific oligonucleotide (ASO) hybridization, allele specific 5′exonuclease detection, sequencing, and/or hybridization.

PCR-based detection means may include amplification of a plurality ofmarkers simultaneously. PCR primers may be selected to generate PCRproducts that do not overlap in size and may be analyzed simultaneously.Alternatively, one may amplify different markers with primers that aredifferentially labeled. Each marker may then be differentially detected.Hybridization-based detection means may allow the differential detectionof multiple PCR products in a sample.

Nucleic acid primers and/or oligonucleotides may be used in conjunctionwith any of the herein described methods and/or kits. The followingoligonucleotides or primers may be present in the herein described kitsand/or used in the herein described methods:

TABLE 2  SNP Primer #1 Primer #2 IL1b_rs ACGTTGGATGAGACCTGTTCCCAGCTTCACGTTGGATGCTCCTGCTACCACTTATTC 1143639 (SEQ ID NO: 19) (SEQ ID NO: 20)IL1b_rs ACGTTGGATGGTGCTCCACATTTCAGAC ACGTTGGATGCAGTTCAGTGATCGTACAG1143634 (SEQ ID NO: 21) (SEQ ID NO: 22) IL1R1_rsACGTTGGATGCTCCTGCAACGGGTAGTC ACGTTGGATGGTGCAAAATTTGTGGAGAG 2228139(SEQ ID NO: 23) (SEQ ID NO: 24) IL1a_rs ACGTTGGATGTTTCACATTGCTCAGGACACGTTGGATGATCTGCACTTGTGATCATG 17561 (SEQ ID NO: 25) (SEQ ID NO: 26)IL1b_rs ACGTTGGATGTGACCGTATATGCTCAGG ACGTTGGATGATAAAATCAGAAGGGCAGC1143633 (SEQ ID NO: 27) (SEQ ID NO: 28) IL1RN_rsACGTTGGATGGCTTGCATCATCCTATTC ACGTTGGATGCTGGTGTTCACACTCTTAG 4252019(SEQ ID NO: 29) (SEQ ID NO: 30) IL1a_rs ACGTTGGATGTGACTGGGTGATTTCACCACGTTGGATGGGGAAAATAGTTCTGGAGG 2071374 (SEQ ID NO: 31) (SEQ ID NO: 32)IL1b_rs ACGTTGGATGCTTTTATCTTCTGCCAGC ACGTTGGATGTGCAATGCGTAGTCTGTAG3917368 (SEQ ID NO: 33) (SEQ ID NO: 34) IL1b_rsACGTTGGATGCTTTTATCTTCTGCCAGC ACGTTGGATGTGCAATGCGTAGTCTGTAG 3917368(SEQ ID NO: 35) (SEQ ID NO: 36)

A probe or oligonucleotide may comprise a SNP corresponding tors1143639^(256T) (as shown in SEQ ID NO:3), rs1143639^(256C) (as shownin SEQ ID NO:4), rs1143634^(401A) (as shown in SEQ ID NO:1),rs1143634^(401G) (as shown in SEQ ID NO:2), rs2228139^(301G) (as shownin SEQ ID NO:5), rs2228139^(301C) (as shown in SEQ ID NO:6),rs17561^(256A) (as shown in SEQ ID NO:7), rs17561^(256C) (as shown inSEQ ID NO:8), rs3917356^(256C) (as shown in SEQ ID NO:9),rs3917356^(256T) (as shown in SEQ ID NO:10), rs1143633^(401T) (as shownin SEQ ID NO:11), rs1143633^(401C) (as shown in SEQ ID NO:12),rs3917368^(301T) (as shown in SEQ ID NO:13), rs3917368^(301C) (as shownin SEQ ID NO:14), rs4252019^(501T) (as shown in SEQ ID NO:15),rs4252019^(501C) (as shown in SEQ ID NO:16), and rs2071374^(301G) (asshown in SEQ ID NO:17), rs2071374^(301T) (as shown in SEQ ID NO:18). Theprobe or oligonucleotide may be a fragment of any one of SEQ NO:1through SEQ NO:18, wherein the fragment comprises the corresponding SNP.The fragment may be between 10 and 500 nucleotides, between 50 and 400nucleotides, between 100 and 300 nucleotides, between 200 and 250nucleotides, between 10 and 50 nucleotides, between 10 and 20nucleotides, between 10 and 30 nucleotides, or between 10 and 40nucleotides in length.

3. METHOD OF TREATMENT

In any patient that carries the PI-marker, an assessment may be made asto whether the subject is an early disease subject, wherein pulmonaryinfection has not occurred, or whether the subject has been colonizedwith a bacterial pathogen. The assessment may indicate an appropriatecourse of preventative or maintenance antibiotic therapy. Antibiotictherapy may be administered in different clinical settings during thelife of a CF subject: (1) during early lung disease a subject mayreceive antibiotics to delay onset of chronic bacterial colonization;(2) after a subject has been colonized with one or more bacterialpathogens, wherein antibiotics may be administered to slow any declinein pulmonary function and reduce frequency and morbidity of pulmonaryexacerbations; and/or (3) during periodic exacerbations in pulmonarysymptoms, wherein intensive antibiotic regimens may be administered torelieve symptomatology and restore pulmonary function to baselinevalues.

a. Predictive Treatment

Provided herein is a method of treating a CF subject having a PI-marker.Antibiotics may be administered to the subject to prevent or delay onsetof bacterial infection. The subject may be undergoing treatment for CF.

The treatment of a subject with a particular therapeutic may bemonitored by determining protein, mRNA, and/or transcriptional level ofa gene. The gene may be in the IL-1 gene cluster. The gene may be anIL-1α gene, IL-1β gene, IL-1 receptor gene, and/or IL-1 receptorantagonist gene. Depending on the level detected, the therapeuticregimen may be maintained or adjusted. The effectiveness of treating asubject with an agent may comprise (1) obtaining a preadministrationsample from a subject prior to administration of the agent; (2)detecting the level or amount of a protein, RNA or DNA in thepreadministration sample; (3) obtaining one or more post-administrationsamples from the subject; (4) detecting the level of expression oractivity of the protein, RNA or DNA in the postadministration sample;(5) comparing the level of expression or activity of the protein, RNA orDNA in the preadministration sample with the corresponding protein, RNA,or DNA in the postadministration sample, respectively; and (6) alteringthe administration of the agent to the subject accordingly.

Cells of a subject may be obtained before and after administration of atherapeutic to detect the level of expression of genes other than thegene of interest to verify that the therapeutic does not increase ordecrease the expression of genes that could be deleterious. Verificationmay be accomplished by transcriptional profiling. mRNA from cellsexposed in vivo to a therapeutic and mRNA from the same type of cellsthat were not exposed to the therapeutic may be reverse transcribed andhybridized to a chip containing DNA from many genes. The expression ofgenes in the treated cells may be compared against cells not treatedwith the therapeutic.

b. Maintenance Therapy

Appropriate antibiotic therapy and/or anti-inflammatory therapy may beessential steps in the management of CF lung infection. Antibioticselection for any given subject in any given setting may be based onperiodic isolation and identification of pathogens from respiratorysecretions and a review of the antimicrobial susceptibility profile forthose pathogens. Antibiotics may be used for outpatient management of CFand/or for the treatment of bacteria associated with pulmonaryexacerbations.

c. Antibiotics and Anti-Inflammatories

An antibiotic may be selected from the following: an aminoglycoside,amoxicillin, levofloxacin, dicloxacillin, cephalexin,amoxicillin/clavulanate, erythromycin, clarithromycin, azithromycin,clindamycin, cefuroxime axetil, cefprozil, cefixime, cefpodoximeproxetil, loracarbef, ciprofloxacin, tobramycin, colistin,trimethoprim/sulfamethoxazole, doxycycline, minocycline, cefazolin,nafcillin, vancomycin, β-lactam, ceftazidime, ticarcillin, piperacillin,imipenem, meropenem, aztreonam, an aminoglyco side, amikacin, merpenem,ceftazidime, chloramphenicol, ticarcillin/clavulanate, aztreonam,imipenem, a polypeptide antibiotic, and/or meropenem. The polypeptideantibiotic may be of the polymyxin class of antibiotics. A broad rangeantibiotic may be used in the regimen. A broad range antibiotic mayinclude levofloxacin or amoxycillin.

An anti-inflammatory agent may be an IL-1 blocker. An IL-1 blocker maybe selected from the following: rilonacept, anakinra, and/orZn-protoporphyrin (ZnPP).

The antibiotic or anti-inflammatory may be formulated for administrationby injection, inhalation or insufflation through the nose or mouth, ororal, buccal, parenteral, or rectal administration. The antibiotic oranti-inflammatory may be formulated for parenteral administration byinjection, e.g., by bolus injection or continuous infusion. Formulationsfor injection may be presented in unit dosage form, e.g., in ampules orin multi-dose containers, with an added preservative. The antibiotic oranti-inflammatory may take such a form as a suspension, solution, oremulsion in oily or aqueous vehicles, and may contain formulating agentssuch as suspending, stabilizing and/or dispersing agents. Antibiotic oranti-inflammatory preparations for oral administration may be suitablyformulated to give controlled release of the antibiotic. For buccaladministration, the antibiotic may take the form of tablets or lozengesformulated in conventional manner. For administration by inhalation, thecompounds for use according to the present invention are convenientlydelivered in the form of an aerosol spray presentation from pressurizedpacks or a nebuliser, with the use of a suitable propellant. In the caseof a pressurized aerosol, the dosage unit may be determined by providinga valve to deliver a metered amount.

An effective dose of the antibiotic may be based upon a culturedetermination of the bacterial type causing the infection. In addition,an antimicrobial susceptibility report may indicate which families ofantibiotic drugs are useful for the particular bacteria recovered fromthe infection. If the cause of the infection is unclear, but suspectedto be due to bacteria, a broad-spectrum antibiotic may be prescribed forcontrolling a wide variety of bacterial types. In general, the compoundsof this invention will be administered in a therapeutically effectiveamount by any of the accepted modes of administration for agents thatserve similar utilities. The actual amount of the compound of thisinvention, i.e., the active ingredient, will depend upon numerousfactors such as the severity of the disease to be treated, the age andrelative health of the subject, the potency of the compound used, theroute and form of administration, and other factors. The drug can beadministered more than once a day, preferably once or twice a day.Therapeutically effective amounts of an antibiotic may range fromapproximately 0.05 mg to 10 g per kilogram body weight of the subjectper day. Antibiotic use and dose regimens as they relate to pulmonaryinfections in CF subjects may be found in Gibson et al. (Pathophysiologyand management of pulmonary infections in cystic fibrosis, Am. J.Respir. Crit. Care Med. 2003 Oct. 15; 168(8):918-51), which isincorporated by reference in its entirety.

4. METHOD OF MONITORING CF

Also provided herein is a method of monitoring a CF subject forpulmonary infection. The CF subject may have been determined to have apredisposition for pulmonary infection. The CF subject may already havea pulmonary infection. It may be desirable to measure the effects oftreatment on CF by treating the patient using a method comprisingmonitoring the lung infection. Monitoring for pulmonary infection, orprogression of pulmonary infection, may include any pulmonary functiontest (PFT), microbial cultures, imaging techniques, inflammatorymarkers, serological markers, and any of several general signs such asexacerbation rate and nutritional status.

5. KIT

Provided herein is a kit, which may be used for diagnosing, monitoring,or treating a pulmonary infection. The kit may comprise a nucleic acidsample collecting means. The kit may also comprise a means fordetermining a marker in an IL-1 gene sequence, a nucleic acid for use asa positive control, and/or a nucleic acids sampling means. The nucleicsampling means may include substrates, such as filter paper, nucleicacid purification reagents, such as reaction buffer, polymerase, anddNTPs. Marker detection means may also be included in the kit. Suchmeans may include, specific restriction enzymes, marker specificoligonucleotides, and degenerate oligonucleotide primers for PCR. Thepositive control may be used for sequence comparison.

The kit may also comprise one or more containers, such as vials orbottles, with each container containing a separate reagent. The kit mayfurther comprise written instructions, which may describe how to performor interpret an assay or method described herein.

The present invention has multiple aspects, illustrated by the followingnon-limiting examples.

EXAMPLES Example 1 UNC and CWRU Study Populations

University of North Carolina and Case Western Reserve (UNC/CWRU) Cohort.For this case-control study, we used the DNA and serum samples from 840patients with CF, enrolled from 44 centers, who were initiallydetermined to be homozygous for the ΔF508 genotype. The diagnosis of CFwas documented in the medical record by the pilocarpine iontophoresissweat test (sweat chloride >60 mmol/L). The 840 patients initiallyenrolled were chosen because their FEV₁ measurements were in the lowestquartile or highest quartile for age among ΔF508 homozygotes; of these,the lung function of 275 patients was classified as severely impaired(lowest quartile) and that of 565 patients as mildly impaired (highestquartile). Quartiles were defined by the Cystic Fibrosis Foundationregistry data classification of pulmonary function testing for the UNCcenter when compared to US CF centers allowing for CF-specific lungfunction classification. The FEV₁ measurement was obtained when thepatient was clinically stable and not during a bronchitic exacerbation,defined as an FEV₁ change of greater than 15% predicted. A total of 32patients were excluded because they had inadequate spirograms (2patients), were found not to be homozygous for the ΔF508 genotype on asubsequent evaluation (8 patients), or did not achieve more than 90%probability of being congruent with others in the severe or mildcategory (22). There were 808 patients in the final data set. No patientwas excluded because of race or ethnic background; 96.7% of the patientswere identified as Caucasian.

Each patient received a unique code that allowed for de-identified dataprocessing to maintain anonymity. Key phenotypic data were obtained fromsource documents, including pulmonary function reports and genotype.Spirometry was performed within this cohort, and the resultant forcedexpiratory curves were evaluated for acceptability, in accordance withcurrent American Thoracic Society (ATS) recommendations. Because forcedexpiratory volume in 1 second (FEV1) is most predictive of survival inCF, it was used as the outcome for phenotype-genotype analysis.Spirometry and flow-volume loops were performed in compliance with ATSguidelines; values were recorded as both absolute value and percentpredicted using standard reference equations. All values fromspirometric testing were recorded in liters (L). Standard referencevalue equations were used to calculate percent of predicted forspirometric values adjusted for age.

Example 2 CHB Study Population

Children's Hospital Boston (CHB) Cohort. To attempt to replicate theresults of the case-control study, we genotyped the SNPs in a secondpopulation of CF patients from CHB using a family-based design. All CFprobands were registered in a clinical and laboratory database andfollowed at CHB from 1993 to 2005. The diagnosis of CF was documented inthe medical record by the pilocarpine iontophoresis sweat test (sweatchloride >60 mmol/L) and/or the presence of 2 CFTR mutations. Over 90%of the CF patients were evaluated in the CF clinic at least once peryear. The yearly visits were prospectively scheduled annualized visitswhere clinical evaluation was performed and laboratory data obtained toinclude pulmonary function testing, sputum culture and serum laboratorymeasures.

We evaluated 126 trios (ascertained by the proband) with a pulmonaryphenotype similar to that used in the UNC/CWRU cohort. Forced expiratoryvolume in 1 second (FEV₁) was determined by standard spirometry, meetingAmerican Thoracic Society criteria; absolute values were converted to apercentage of the predicted volume expected for a healthy individual ofthe same age, sex, and height on the basis of the regression equations.For each patient, we extracted all laboratory values and lung functiontest results from the medical record when the patient was at his or herstable baseline and not during a pulmonary exacerbation. A bronchiticexacerbation was defined as worsening of symptoms, as indicated bydeclining lung function and FEV₁ change of greater than 15% predicted,because such a decrease is a strong predictor of clinician-diagnosedpulmonary exacerbation.

We identified eligible CF patients and collected laboratory data fromthe clinical laboratory database at CHB. Specifically, for pulmonaryfunction testing, microbiologic and genotype data were extracted anddownloaded into an ORACLE database. A structured query languagereporting tool was run to join the hospital-wide laboratory valuesrequested to the CF patient population followed at CHB. In the CHBcohort, we had multiple laboratory and pulmonary function measurementsspanning 13 years and were able to analyze the patients' PFTmeasurements in both categorical and longitudinal analyses. For thecategorical lung function analysis, each patient's FEV₁ value wasassigned a disease severity group based on FEV₁ values using the ESCFclassification for patients in four age groups: 6-12 yrs (severe,FEV₁≦88.7% predicted; moderate, >88.7-94.5%; mild >94.5-99.0%; verymild/normal, >99.0%); 13-17 yrs (severe, FEV₁≦76.5% predicted;moderate, >76.5-81.1%; mild >81.1-87.7%; very mild/normal, >87.7%);18-29 yrs (severe, FEV₁≦58.1% predicted; moderate, >58.1-63.9%;mild >63.9-70.7%; very mild/normal, >70.7%); and >30 yrs (severe,FEV₁≦45.5% predicted; moderate, >45.5-50.9%; mild >50.9-59.8%; verymild/normal, >59.8%). For the analysis, a child aged 12.9 would have anage of 12 because we used a “floor” statistical function that rounds theage down to the integer. CF patients in the very mild/normal and themild severity group were pooled for analysis and compared to moderateand severe disease groups, which were also combined. Methods forascertaining sputum culture in the CHB cohort included both deep throatand sputum cultures. Colonization was defined as one positivemicrobiologic growth on culture. Given the method for extracting datafrom various electronic sources and merging them, it was not possible toobtain symptom history or medication information. However, as Children'sHospital Boston is an accredited CF Care Center, patients receivedstandard CF care as outlined by the CF Consortium guidelines. Approvalby the Institutional Review Board was obtained, and we received informedconsent from all subjects in the cohorts.

Example 3 SNP Genotyping and Association Analysis

We investigated the IL1-gene cluster on chromosome 2, based on theNational Center for Biotechnology Information (NCBI) dbSNP build 125. Wegenotyped 58 SNPs in the IL-1 gene cluster in 808 CF subjects fromUNC/CWRU cohort. SNPs in candidate genes were selected for genotyping onthe basis of one of three criteria: r² value of at least 0.7 (forlinkage disequilibrium [LD]-tagging SNPs), allele frequency of at least10% in European-American populations, and/or causing a non-synonymousalteration in the amino acid sequence of the coded protein. All SNPswere verified by review of documentation in three databases—dbSNP, theInnate Immunity (http://innate.immunity.net), and Seattle SNPs(http://pga.mbt.washington.edu) program for genomic applications (PGA)web sites. SNP genotyping was performed using the standard protocol forthe iPLEX assay on a Sequenom MassARRAY MALDI-TOF mass spectrometer 26(Sequenom, San Diego, Calif.) or TaqMan assays 27 (Applied Biosystems,Foster City, Calif.).

Single SNP association analyses were conducted using logistic regressionfor dichotomous outcomes and linear regression for continuousphenotypes. All population-based statistical analyses were performedusing SAS statistical software (SAS Institute Inc., Cary, N.C.), whileall family-based association testing was performed using FBAT 28 andPBAT. In the 2 cohorts, we evaluated a potential association between IL1polymorphisms and lung function in CF in the following way. In thescreening step, we tested for association between the selected SNPs andlung disease severity using extremes of pulmonary function measurements,as defined by Drumm and colleagues, in a case-control analysis in theUNC/CWRU CF subjects. In the replication cohort (CHB), we tested forassociation with affection status (an allele transmission distortion) asdefined by the ascertainment of the proband in a family-based analysis,using the FBAT approach. As a secondary analysis, we also used thequalitative lung phenotype, with severity defined using extremes ofpulmonary function measurement determined by ESCF classification, in afamily-based analysis. Additionally, since quantitative lung functiondata were available in the CHB cohort, we evaluated the associationbetween the selected SNPs and lung function in a longitudinal analysis,incorporating quantitative pulmonary function measurements over thefirst 5 study visits. Only the first five annualized study visits wereincluded to minimize the number of missing subjects (datacompleteness >90% over the first 5 study visits) and minimize anypotential cohort effect. The longitudinal analysis was conducted in SAS(version 9.1, Cary, N.C.) using a mixed model, with fixed effects forthe SNP, subject age at baseline, and time under study. Randomintercepts and slopes were modeled for each subject. In summary, weevaluated two CF populations (UNC/CWRU and CHB) and threephenotypes—analysis of extremes of lung function using dichotomized lungfunction severity (in UNC/CWRU and CHB cohorts), affectionstatus/transmission distortion (CHB cohort), and longitudinal lungfunction measures (CHB cohort) to assess whether the IL-1 family genecluster has an effect on CF lung disease.

Example 4 Associations Between IL-1 SNPs and Lung Function

A total of 808 UNC/CWRU subjects were analyzed. The mean age for 263patients classified with severe lung disease was 16.2±4.1 years, and themean age for 545 patients classified with mild lung disease was 28.6±9.7years (Table 2). Males made up 49.4% of the severe disease group and55.6% of the mild disease group. All of the analyzed patients were ΔF508homozygous and therefore pancreatic-insufficient. Over 80% of the cohorthad positive cultures for P. aeruginosa. The mean FEV₁% predicted was46.6±16.1 in the severe group and 72.4±28.1 in the mild group. The rateof FEV₁ decline (percent/year) in the severe group was 3.65±2.20 and1.35±1.51 in the mild group.

TABLE 2 SEVERE MILD IMPAIRMENT IMPAIRMENT VARIABLE (N = 263) (N = 545) PVALUE AGE RANGE 8-25 15-55 AGE MEAN 16.2 +/− 4.1  28.6 +/− 9.7  <0.001SEX (% MALE) 49.4 55.6 0.10 FEV1 (% OF 46.6 +/− 16.1 72.4 +/− 28.1<0.001 PREDICTED VALUE FEV1 DECLINE 3.65 +/− 2.20 1.35 +/− 1.51 <0.001(%/YEAR) MEDIAN 31.4 56.6 <0.001 PREDICTED SURVIVAL BODY-MASS 19.6 +/−21.7 44.0 +/− 26.1 <0.001 INDEX (PERCENTILE) POSITIVE TEST 89.0 86.10.25 FOR P. AERUGINOSA (%) DIABETES 15.6 24.0 0.006 MELLITUS ASTHMA 19.422.0 0.39

In the replication cohort from CHB, a total of 126 trios were analyzed,with a mean age of 10 years ±6.46 years for the CF patients when thefirst clinical values were analyzed (Table 3). This cohort was 53% maleand 47% female. Forty-one percent of the patients were DF508 homozygousand 40% were heterozygotes. Ninety-five percent of the cohort waspancreatic-insufficient, and 92% had positive cultures for P.aeruginosa, of which 70% were positive for mucoid P. aeruginosa. Themean predicted rate of decline in FEV₁ was −2.29±3.76 (percent/year),consistent with an average decline in FEV₁ percent predicted of 2.5-2.6(percent/year) for CF patients 31. Table 4 illustrates the pulmonaryfunction data for the 126 CF subjects obtained at the first 5 clinicalvisits and stratified by age. In Table 4, there is a value for eachsubject per year. For example, if a subject had data each year from theage of 11-14, the subject was represented four times in the table. Theywere represented twice in the 6-12 age category and twice in the 13-17age category.

TABLE 3 N % Mean Min Max Trios 126 Female 59 47 Age—at consent 126 18.5+/− 8.7 8 45 Age—on first 126 10.0 +/− 6.5 1 36 clinical values  1-12 9575 13-17 17 13 18-29 11 8 30+ 3 2 Genotype ΔF508 52 41 Homozygous ΔF50851 40 Heterozygous Other 15 12 Unknown 8 6 Pancreatic Insufficient 12095 Sweat Chloride 119 94 104.3 +/− 16.8 40 143 FEV1 (% predicted) 559 92.9 +/− 19.6 24 162 % change FEV1 %/yr 559 −2.3 +/− 3.6 −14.3 0

TABLE 4 Age and Number of Patient Visits(%)^(b) Disease Row Severity^(a)6-12 13-17 18-29 >30 yrs Totals Normal/  192(34%)  53(9%) 66(12%) 17(3%) 328(59%) very mild Mild  48(9%)  11(2%)  6(1%)  2(0%)  67(12%) Moderate 38(7%)  8(1%)  1(0%)  2(0%)   49(9%) Severe  96(17%)  14(3%)  4(1%) 1(0%)  115(21%) Totals 374(67%) 86(15%) 77(14%) 22(4%) 559(100%)^(a)Each patient was assigned a disease assigned a disease severitygroup based on FEV1 values using the Epidemiological Study of CysticFibrosis (ESCF) classification for patients in four age groups: 6-12 yrs(severe, FEV1 ≦ 88.7% predicted; moderate, >88.7-94.5%;mild >94.5-99.0%; very mild/normal, >99.0%); 13-17 yrs (severe, FEV1 ≦76.5% predicted; moderate, >76.5-81.1%; mild >81.1-87.7%; verymild/normal, >87.7%); 18-29 yrs (severe, FEV1 ≦ 58.1% predicted;moderate, >58.1-63.9%; mild >63.9-70.7%; very mild/normal, >70.7%)and >=30 yrs (severe, FEV1 ≦ 45.5% predicted; moderate, >45.5-50.9%;mild >50.9-59.8%; very mild/normal, >59.8%). ^(b)Excludes 47 visits forsubjects when FEV1% predicted was missing.

We confined our analyses to self-described Caucasians to minimize thechance of identifying false associations due to populationstratification in the case-control analysis. In addition, power todetect associations in other racial groups is low due to small samplesizes, particularly in CF, where the affected cohort is mostly Caucasian32.

A total of 58 SNPs in the IL-1 gene cluster were initially investigatedin the UNC/CWRU cohort; 9 SNPs were then investigated in the CHB cohort.Across both cohorts, none of the selected SNPs showed significantoverall departure from Hardy Weinberg equilibrium. Genotyping qualityfor both Sequenom and TaqMan assays was high, with an average completionrate of 98%, no discordances on repeat genotyping of a random 10% of thecohort, and a low rate of Mendelian inconsistencies.

Analysis of extremes of lung function: We tested for an associationbetween the selected SNPs and lung disease severity in subjects with“mild” (n=545) or “severe” (n=263) illness by Fisher's exact andArmitage trend testing. As shown in Table 5, three SNPs in the gene forIL1β (IL1B), rs1143633, rs1143639 and rs3917356, as well as a SNP inIL1-RN (the gene for the receptor antagonist for IL-1), rs4252019, weresuggestive of an association with lung disease severity in CF (p<0.10).While not significant in the non-stratified analysis, when stratified bygender, other SNPs were associated with lung disease severity: anotherSNP, rs17561, in the gene for IL-1α (IL1A) (p<0.05 in the males), oneSNP in the IL1B gene rs1143634 (p<0.07 in the females), and one SNPrs2228139 in the IL1-R1 gene (p<0.05 in the females). To furtherdetermine which SNPs to genotype in a family-based analysis, we fit alogistic regression model for each SNP, calculating the odds of severeversus mild CF for each genotype in all 58 SNPs initially screened byFisher's exact and Armitage testing. The analysis with the logisticregression models confirmed the Armitage testing. Eight SNPs showed anOR>1.5 (rs17561, 3917356, 1143633, 1143634, 1143639, 3917368, 2228139,and 4252019), indicating a greater odds of having severe versus mild CFlung disease when comparing genotyping categories (data not shown). Foran OR>1, the genetic variant is associated with disease and in this caseworse pulmonary function. One SNP, rs 2071374 in the gene for IL-1α(IL1A), had an OR≦0.5 indicating greater odds of having mild CF lungdisease when comparing genotyping categories. With these promisingresults, we proceeded to evaluate 9 SNPs using a family-based analysisin a second population.

TABLE 5 Significant associations of IL-1 genotypes and mild (highestquartile*) versus severe (lowest quartile*) pulmonary functionimpairment in the UNC/CWRU cohort MAF MAF Fisher's Fisher's SNP (general(CF P Value P value Armitage Gene Location SNP rs# MA population)population) Fisher's P Value Male Female P Value IL1α Intron 4 2071374 G0.30 0.30 0.102 0.497 0.163 0.091 IL1α Exon 5 17561 A 0.33 0.29 0.4150.008 0.015 0.248 IL1β Intron 3 3917356 C 0.43 0.47 0.093 0.290 0.3060.035 IL1β Intron 4 1143633 T 0.45 0.38 0.067 0.329 0.157 0.073 IL1βExon 5 1143634 A 0.25 0.23 0.120 0.350 0.069 0.064 IL1β Intron 6 1143639T 0.28 0.23 0.057 0.289 0.039 0.038 IL1β 3′UTR 3917368 T 0.46 0.38 0.1090.523 0.125 0.105 IL1R1 Exon 4 2228139 G 0.11 0.07 0.186 1.0 0.035 0.057IL1RN Intron 4 4252019 T 0.09 0.14 0.048 0.572 0.005 0.015

With respect to Table 5, SNP rs #-refSNP number, MA means minor allele,MAF means minor allele frequency in the general and CF populations, andp is the p-value obtained from linear regression under an additive modelusing Fisher's and Armitage testing. * Quartiles are based on the ESCFclassification of pulmonary function testing for the UNC/CWRU centerwhen compared to US CF centers 19. For the UNC/CWRU case-control data,p-values were obtained from a Fisher's exact test and Armitage trendcomparing genotype counts in cases (severe CF) to controls (mild CF).There is an overtransmission of the minor allele in the severe CF casesfor these SNPs.

Example 5 Analysis of Extremes of Lung Function in UNC/CWRU Cohort

SNP characteristics (allele frequency and Hardy-Weinberg equilibrium)for each SNP were assessed. Selected SNPs in candidate genes weregenotyped in 808 ΔF508 homozygotes with “severe” or “mild” lung disease,as defined by the lowest or highest quartile of forced expired volume(FEV1) for age. We tested for association between the selected SNPs andlung disease severity in subjects with “mild” (n=545) and “severe”(n=263) illness by both Fisher's exact and Armitage trend testing.Multivariable associations between individual SNP and FEV₁ percentpredicted in the presence of potential confounders (age and gender) weretested using a general linear model. Genotypes were coded assuming anadditive genetic model. For complex trait statistical models in which 2or more loci may be involved in disease susceptibility, additive models,in which the allele-specific risks of disease are associated with themultilocus genotypes across different loci, can be modeled as sums offactors for each genotype at each locus. Odds ratios comparing severeversus mild CF were also calculated for each genotype (with thehomozygote wild-type as the reference group) for all 58 SNPs, todetermine whether significant Fisher's exact and Armitage testscorresponded to a clinically meaningful change in the odds of severe CF.The Fisher's test was conducted to assess the magnitude of effect andexamine the effect of each genotyped on risk, without imposing anyassumptions about the genetic model. From these analyses, 9 SNPs withOR≦0.5 or >1.5 showing evidence of association and moderate effect sizeswere selected for further testing in subjects recruited from Children'sHospital Boston.

Example 6 Analysis of Extremes of Lung Function in CHB Cohort

For the familial data (CHB), 9 SNPs were tested using an additive modelfor evidence of association with the diagnosis of CF in the proband. Thepurpose was to determine whether any of the SNP alleles weresignificantly over- or under transmitted to the proband.

Analysis of extremes of lung function in CHB cohort: We tested forassociation between the selected SNPs and lung disease severity insubjects with “mild” or “severe” illness as defined by an assigneddisease severity group, based on FEV₁ values and using the ESCF patientclassification for patients (described in methods). Due to the smallsample size in the CHB cohort, we were unable to analyze on the subjectsin either of the “extreme” categories of normal/mild or moderate/severelung impairment. Thus, the ESCF classification was collapsed into twocategories: normal/mild and moderate/severe. In the CHB family analysis,p-values were obtained from an FBAT statistic comparing observed toexpected allele transmission from parents to CF probands withnormal/mild or moderate/severe lung function impairment at the firststudy visit.

Longitudinal analysis of FEV₁% predicted in the CHB cohort:Longitudinally measured lung function phenotypes were available in thiscohort. As some of the associations observed in the UNC/CWRU cohortdisplayed differential effects by gender, both overall andgender-stratified analyses were conducted.

To maximize the power to detect an association, we analyzedpercent-predicted FEV₁ with a multivariate population-based analysis(the offspring genotype, rather than parent-child allele transmissions,was the predictor of interest). A mixed model (SAS, Cary N. C.) was fit,including a random effect for each subject and for time sincerecruitment. Each SNP was tested separately, assuming either anadditive, dominant or recessive genetic model as a fixed effect, alongwith age at recruitment, gender, and time since recruitment. As ΔF508polymorphisms in the CFTR gene are the most common cause of CF, theanalysis was repeated with adjustment for the presence or absence of 2copies of ΔF508 alleles using a recessive genetic model.

Finally, we examined the relationship between the two SNPs of interest,rs1143634 and rs1143639, and the presence of non-mucoid or mucoid P.aeruginosa in the CHB cohort. Methods for ascertaining culture includedboth deep throat and sputum cultures. Colonization was defined as onepositive microbiologic growth on culture. Two sets of analyses wereconducted. Initially, logistic regression models were fit to determinewhether rs1143634 or rs1143639 genotypes predicted the presence orabsence of non-mucoid or mucoid P. aeruginosa, after adjusting for ageat first study visit. Second, survival analyses (also adjusting for ageat first study visit) were performed to test whether specific rs1143634or rs1143639 genotypes predicted time of onset of non-mucoid or mucoidP. aeruginosa. The analysis was conducted using a Cox-proportionalhazards model was fit (using proc phreg in SAS) to test this hypothesisin both the overall group and gender-stratified groups.

Affection status analysis (transmission distortion): We next evaluated126 trios in a second population of CF patients from CHB using afamily-based design. Due to the gender-specific differences observed forSNPs selected from the UNC/CWRU sample for replication, the associationanalysis of affection status in the CHB cohort was conducted in both theoverall and gender-stratified cohort. Under an additive model, two ofthe SNPs associated with the IL1B gene, rs1143634 and rs1143639, weresuggestive of an association in the gender-stratified analysis (p<0.05).None of the other 7 SNPs was nominally significant (all p>0.05) ineither the overall or stratified cohort.

As shown in Table 6, in the subgroup analysis, the p-values for thefemales is significant (p<0.05), demonstrating a strong effect size,given the small number of informative trios in the CHB cohort (thenumber of informative trios for females was 29 for both SNPs). Thedirection of the association is consistent across the UNC/CWRU and CHBcohorts; the frequency of the minor allele is overrepresented in theUNC/CWRU severe CF cases (Table 5) and over-transmitted to femaleprobands in the CHB cohort (Table 6). Therefore, the association issuggestive, given the consistency across studies and the relativelysmall number of female subjects (n=366 in UNC/CWRU and informativetrios=29 in CHB), and p-values (p<0.10).

TABLE 6 Analysis of Affection Status in Children's Boston Cohort FemalesMales Overall Nominal Nominal Nominal Minor N info. 2-sided N info.2-sided N info. 2-sided SNP Allele families p-value families p-valuefamilies p-value rs1143634 A 29 0.016 43 0.285 66 0.463 rs1143639 T 290.016 42 0.225 65 0.527

With respect to Table 6, P-values were obtained from an FBAT statisticcomparing observed versus expected (assuming Mendelian) transmissionfrom parents to affected offspring. All probands in this analysis haveCF. In females the minor allele for both SNPs is overtransmitted(p=0.016).

Given the consistent association in females, the p-values for rs1143634and rs1143639 from Fisher's test of association in the UNC/CWRU cohortand p-values from the family-based association test in the CHB cohortwere combined using Fisher's combined probability test 33. The jointp-values for SNPs rs 1143634 and rs1143639 from the overall test ofassociation for the two studies, as well as the analysis in males, werenot significant. For females, the unadjusted joint p-values were 0.0086and 0.0052 in rs 1143634 and rs1143639, respectively. After a falsediscovery rate (FDR) correction was applied to the UNC/CWRU cohort,accounting for the 58 SNPs initially tested 34, the adjusted p-valueswere 0.059 (rs 1143634) and 0.052 (rs1143639).

Analysis of extremes of lung function in the CHB cohort: We alsoevaluated a dichotomous phenotype in the CHB cohort, based on FEV1 ESCFcategories, similar to the categorization of the UNC/CWRU cohort. Tomaximize information from an increased sample size that has fewerquantitative measures, the UNC/CWRU analysis compared extremes of lungfunction, that is, severely impaired (lowest quartile) with mildlyimpaired (highest quartile). For the CHB family data, which are from asmaller sample than the UNC/CWRU cohort but include additionallongitudinal quantitative FEV₁ measurements, p-values were obtained froman FBAT statistic comparing observed to expected allele transmissionfrom parents to CF probands with collapsed ESCF categories ofnormal/mild or moderate/severe lung function impairment. There was noassociation in either the overall or gender-stratified analysis in theCHB cohort (data not shown). However, this may be due to the smallsample size, particularly in the gender-stratified analysis. The numberof informative families in each analysis ranged from 55 (in the overallanalysis) to 24 (in the gender-stratified analysis for females).

Longitudinal analysis of FEV₁% predicted in the CHB cohort: To extractthe most information from our cohort, we also conducted apopulation-based longitudinal analysis. Due to the unavailability oflongitudinal lung function data in the UNC/CWRU cohort, additionalanalyses of lung function could be conducted only in the CHB cohort. Thetwo SNPs of interest in the IL1B gene from the affection statusanalysis, rs1143634 and rs1143639, were tested for association using theFEV₁% predicted phenotype, measured at the first 5 study visits.

FIGS. 1 and 2 present the age- and gender-adjusted means for FEV1%predicted for each genotype for IL1B SNPs rs1143634 and rs1143639. InFIG. 1, 56 patients are homozygous major for the GG genotype, and 43 areheterozygous/homozygous minor with either AG or AA genotype. In FIG. 2,57 patients are homozygous for the major allele, CC and 42 patients areheterozygous/homozygous minor for the CT or TT genotype. The averagelength of time from the first study visit to the second study visit was1.4 years, and the mean length of time between subsequent visits was oneyear. The mean length of time over all 5 of the study visits was 4.5years. The calculated means are limited to subjects with complete datafor the first 5 study visits, to limit any potential cohort effects.Displayed above each study visit (on the x-axis) are the correspondingunivariate effect size estimates and p-values for each genotype group.There is a difference in the FEV₁% predicted in subjects with one or twocopies of the minor A or T allele for rs1143634 or rs1143639,respectively. In the overall group, for rs1143634, the mean differencein FEV₁ between the GG and AG/AA genotype groups across the five studyvisits was 5.6%, after adjusting for age and gender. For rs1143639, themean difference in FEV₁ between the CC and CT/TT genotype groups acrossthe five study visits was 6.7%, after adjusting for age and gender. Wewould expect similar results for these two SNPs, because the linkagedisequilibrium (LD) between the two markers is similar (D=−0.171, D′=1.0and R2=0.98). The longitudinal model adjusted for age at the first visitas well as time in follow-up, to reflect the variable ages and toaccount for the effect of age on FEV₁. Age was not significant acrossthe different genotype groups. We also analyzed the means by genotype(homozygote major allele versus heterozygote and homozygote minorcombined) and t-tests of the difference in ages (at each study visit)across groups. None of the differences was significant (data not shown).

Table 7 presents the multivariate results for the dominant model,adjusting for age and gender in the overall group, and for age in thegender-stratified analysis. There is a trend toward decreasing FEV₁%predicted for the heterozygote or homozygote minor allele. The overallp-value (a test of whether the mean FEV₁% predicted differs across themajor allele homozygotes versus the heterozygotes and minor allelehomozygotes combined) was 0.06 for SNP rs1143634 and 0.05 for SNPrs1143639. Therefore, in the longitudinal analyses, having one or twocopies versus none of the minor allele shows evidence of association(p<0.10) for both of the SNPs within the IL1B gene and lung functiondecline. The analysis of the CHB cohort was repeated with adjustment forΔF508 alleles, assuming a recessive genetic model. The presence of ΔF508mutations was not associated with FEV₁% predicted and did not affect therelationship between SNPs rs1143634 or rs1143639 and FEV₁% predicted.The magnitude of the effect size estimates and p-values for SNPsrs1143634 and rs1143639 did not substantially change after inclusion ofΔF508 in the model (data not shown).

TABLE 7 Population-based Analysis for a mean decrease in FEV1 %predicted RS1143634 RS1143639 Time point (AG/AA vs. GG) (CT/TT vs CC)All 5 visits Beta p Beta p Female −7.21 0.06 −7.05 0.06 Male −3.29 0.32−4.10 0.29 Overall −5.17 0.06 −5.27 0.05

With respect to table 7, all analyses are adjusted for age. Overallanalysis is also adjusted for gender. The overall p values test whethermean FEV₁% predicted differs across the major allele homozygotes versusthe heterozygotes and minor allele homozygotes combined.

Finally, we examined the relationship between the two IL1B-associatedSNPs of interest, rs1143634 and rs1143639, and the presence ofnon-mucoid or mucoid P. aeruginosa. Neither the logistic regressionanalyses nor the Cox model showed a relationship between rs1143634 orrs1143639 genotypes and the presence or onset of mucoid Pseudomonas(data not shown). There was no significant association between the SNPsand presence of non-mucoid P. aeruginosa. However, in the overall(non-stratified analysis), for both rs1143634 and rs1143639, thepresence of one or two copies of the minor allele was associated with alater onset of non-mucoid P. aeruginosa, with hazard ratios of 0.624 and0.661, and p-values of 0.039 and 0.068, respectively.

1.-16. (canceled)
 17. A method of treating a pulmonary infection in asubject, comprising administering an anti-infection agent to a cysticfibrosis subject in need thereof, wherein the genome of the subjectcomprises a pulmonary infection marker selected from the groupconsisting of rs1143639^(256T), rs1143634^(401A), rs2228139^(301G),rs17561^(256A), rs3917356^(256C), rs1143633^(401T), rs391736^(301T),rs4252019^(501T), and rs2071374^(301G), and wherein the pulmonaryinfection marker indicates that the subject has a predisposition forpulmonary infection.
 18. The method of claim 17, wherein theanti-infection agent is an anti-inflammatory.
 19. The method of claim18, wherein the anti-inflammatory is an IL1 blocker.
 20. The method ofclaim 19, wherein the IL1 blocker is selected from the group consistingof rilonacept, anakinra, and Zn-protoporphyrin (ZnPP). 21.-23.(canceled)
 24. The method of claim 17, wherein the pulmonary infectionis associated with bacterial lung colonization.
 25. The method of claim24, wherein the bacterium is selected from the group consisting of P.aeruginosa, S. aureus, H. influenzae, B. cepacia, methicillin-resistantS. aureus, S. maltophilia, and A. xylosoxidans
 26. The method of claim17, wherein the marker is detected in a nucleic acid-containing sampleobtained from the subject, and wherein the detection comprises: (a)providing a nucleic acid-containing sample obtained from the subject;(b) amplifying a nucleic acid comprising the marker; and (c) detectingthe amplified nucleic acids, thereby detecting the marker.
 27. Themethod of claim 26, wherein the marker is detected by sequencing. 28.The method of claim 26, wherein the marker is amplified using a pair ofprimers comprising the sequences selected from the group consisting ofSEQ ID NO:19, SEQ ID NO:20, SEQ ID NO:21, SEQ ID NO:22, SEQ ID NO:23,SEQ ID NO:24, SEQ ID NO:25, SEQ ID NO:26, SEQ ID NO:27, SEQ ID NO:28,SEQ ID NO:29, SEQ ID NO:30, SEQ ID NO:31, SEQ ID NO:32, SEQ ID NO:33,SEQ ID NO:34, SEQ ID NO:35, and SEQ ID NO:36.
 29. The method of claim26, wherein the amplified nucleic acids are detected by hybridizing anoligonucleotide probe to the amplified product.
 30. The method of claim29, wherein the probe is labeled with a detectable label.
 31. The methodof claim 29, wherein the probe is an oligonucleotide comprising a SNPselected from the group consisting of rs1143639^(256T),rs1143634^(401A), rs2228139^(301G), rs17561^(256A), rs3917356^(256C),rs143633^(401T), rs3917368^(301T), rs4252019^(501T), andrs2071374^(301G).
 32. The method of claim 17, wherein the presence of amarker selected from the group consisting of rs3917356^(256C),rs1143633^(401T), rs4252019^(501T), and rs1143639^(256T) is diagnosticof the subject having a predisposition for severe pulmonary infection.33. The method of claim 17, wherein the presence of rs2071374^(301G) isdiagnostic of the subject having a predisposition for mild pulmonaryinfection.